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MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

Fredrik Ronquist; Maxim Teslenko; Paul van der Mark; Daniel L. Ayres; Aaron E. Darling; Sebastian Höhna; Bret Larget; Liang Liu · Systematic Biology · 2012

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Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

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APA 7

Ronquist, F, Teslenko, M, Mark, P. V. D, Ayres, D. L, Darling, A. E, Höhna, S, Larget, B, & Liu, L. (2012). MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space. https://doi.org/10.1093/sysbio/sys029

MLA

Ronquist, Fredrik, et al. "MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space." 2012. https://doi.org/10.1093/sysbio/sys029.

Chicago

Ronquist, Fredrik, Maxim Teslenko, Paul van der Mark, Daniel L. Ayres, Aaron E. Darling, Sebastian Höhna, Bret Larget, and Liang Liu. 2012. "MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space.". https://doi.org/10.1093/sysbio/sys029.

Harvard

Ronquist, F. et al. 2012, MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space, Systematic Biology, available at: https://doi.org/10.1093/sysbio/sys029 [Accessed 8 Aug. 2026].

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Title
MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space
Author / contributors
Fredrik Ronquist; Maxim Teslenko; Paul van der Mark; Daniel L. Ayres; Aaron E. Darling; Sebastian Höhna; Bret Larget; Liang Liu
Publisher
Systematic Biology
Publication year
2012
Language
English

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